Datasets:
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| license: cc-by-4.0 | |
| task_categories: | |
| - text-generation | |
| language: | |
| - pt | |
| tags: | |
| - pretraining | |
| - pt-pt | |
| - Portugal | |
| - bagaco-mix | |
| - arxiv:2603.03543 | |
| - arxiv:2602.05879 | |
| - arxiv:2503.10267 | |
| - arxiv:2107.06499 | |
| - arxiv:2201.06642 | |
| - arxiv:1911.02116 | |
| pretty_name: Bagaco4, o maior corpo publico de pré-treino em português (pt-pt) | |
| size_categories: | |
| - 10M<n<100M | |
| Corpo público de pré-treino dedicado exclusivamente ao português de europeu (pt-PT). | |
| O corpos foi curado de modo a procurar um bom alinhamento com o português usado em Portugal, e minimizar as contaminações de outras variantes da língua ou traduções automáticas de baixa qualidade. | |
| A principal inovação aplicada ás várias versões do bagaco, consiste na classificação prévia do texto de todos os documentos com um score pt-pt, e extrair apenas os documentos que atingem o limiar que garante um score pt-pt superior a 0.90. | |
| Esta versão está segmentada por níveis de qualidade. Este formato apresenta uma ligeira vantagem para a constituição de datasets de pré-treino (com ramping) adaptados ao modelo a treinar. | |
| | edu | pt-pt | docs | chars | words | tokens1 | tokens2 | | |
| |---|---|---|---|---|---|---| | |
| | 5 | 0.8933 | 128,498 | 598,609,752 | 96,096,649 | 151 748 724 | 167,413,547 | | |
| | 4 | 0.8958 | 2,574,687 | 19,598,337,214 | 3,165,154,084 | 4,788,631,045 | 4,303,521,535 | | |
| | 3 | 0.9040 | 5,811,431 | 39,792,992,065 | 6,343,431,560 | 9,510,608,456 | 8,215,187,365 | | |
| | 2 | 0.9290 | 13,738,836 | 53,091,805,170 | 8,557,967,628 | 12,391,659,157 | 12 156 495 527 | | |
| | 1 | 0.9390 | 31,443,575 | 73,734,288,823 | 11,826,372,987 | 17,637,450,554 | 17,987,353,947 | | |
| | 0 | 0.9184 | 44,850,283 | 120,304,072,247 | 19,438,743,284 | 30,155,035,328 | 32,662,463,995 | | |
| | Total | - | 98,547,310 | 307,120,105,271 | 49,427,766,192 | 74 635 133 264 | 75,492,435,916 | | |
| tokens1: nanochat rustbpe 32k dic | |
| tokens2: eurollm | |
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| ## Referências | |
| Este corpo foi produzido pela seleção de vários corpos pelo que a utilização implica a boa prática de citar também os trabalhos originais: | |
| Gigaverbo-v2 | |
| ```bibtex | |
| @misc{correa2026tucano2cool, | |
| title={{Tucano 2 Cool: Better Open Source LLMs for Portuguese}}, | |
| author={Nicholas Kluge Corr{\^e}a and Aniket Sen and Shiza Fatimah and Sophia Falk and Lennard Landgraf and Julia Kastner and Lucie Flek}, | |
| year={2026}, | |
| eprint={2603.03543}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL}, | |
| url={https://arxiv.org/abs/2603.03543}, | |
| } | |
| ``` | |
| EuroWeb-2512 | |
| ```bibtex | |
| @misc{ramos2026eurollm22btechnicalreport, | |
| title={EuroLLM-22B: Technical Report}, | |
| author={Miguel Moura Ramos and Duarte M. Alves and Hippolyte Gisserot-Boukhlef and João Alves and Pedro Henrique Martins and Patrick Fernandes and José Pombal and Nuno M. Guerreiro and Ricardo Rei and Nicolas Boizard and Amin Farajian and Mateusz Klimaszewski and José G. C. de Souza and Barry Haddow and François Yvon and Pierre Colombo and Alexandra Birch and André F. T. Martins}, | |
| year={2026}, | |
| eprint={2602.05879}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL}, | |
| url={https://arxiv.org/abs/2602.05879}, | |
| } | |
| ``` | |
| HPLT2.0_cleaned | |
| ```bibtex | |
| @inproceedings{burchell-etal-2025-expanded, | |
| title = "An Expanded Massive Multilingual Dataset for High-Performance Language Technologies ({HPLT})", | |
| author = {Burchell, Laurie and | |
| de Gibert, Ona and | |
| Arefyev, Nikolay and | |
| Aulamo, Mikko and | |
| Ba{\~n}{\'o}n, Marta and | |
| Chen, Pinzhen and | |
| Fedorova, Mariia and | |
| Guillou, Liane and | |
| Haddow, Barry and | |
| Haji\({\v{c}},\) Jan and | |
| Helcl, Jind\({\v{r}}\)ich and | |
| Henriksson, Erik and | |
| Klimaszewski, Mateusz and | |
| Komulainen, Ville and | |
| Kutuzov, Andrey and | |
| Kyt{\"o}niemi, Joona and | |
| Laippala, Veronika and | |
| M\({\ae}\)hlum, Petter and | |
| Malik, Bhavitvya and | |
| Mehryary, Farrokh and | |
| Mikhailov, Vladislav and | |
| Moghe, Nikita and | |
| Myntti, Amanda and | |
| O{'}Brien, Dayy{\'a}n and | |
| Oepen, Stephan and | |
| Pal, Proyag and | |
| Piha, Jousia and | |
| Pyysalo, Sampo and | |
| Ram{\'i}rez-S{\'a}nchez, Gema and | |
| Samuel, David and | |
| Stepachev, Pavel and | |
| Tiedemann, J{\"o}rg and | |
| Vari\({\v{s}},\) Du\({\v{s}}\)an and | |
| Vojt\({\v{e}}\)chov{\'a}, Tereza and | |
| Zaragoza-Bernabeu, Jaume}, | |
| editor = "Che, Wanxiang and | |
| Nabende, Joyce and | |
| Shutova, Ekaterina and | |
| Pilehvar, Mohammad Taher", | |
| booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", | |
| month = jul, | |
| year = "2025", | |
| address = "Vienna, Austria", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/2025.acl-long.854/", | |
| doi = "10.18653/v1/2025.acl-long.854", | |
| pages = "17452--17485", | |
| ISBN = "979-8-89176-251-0", | |
| } | |
| ``` | |
| CrawlPT_dedup | |
| ```bibtex | |
| @inproceedings{garcia-etal-2024-robertalexpt, | |
| title = "{R}o{BERT}a{L}ex{PT}: A Legal {R}o{BERT}a Model pretrained with deduplication for {P}ortuguese", | |
| author = "Garcia, Eduardo A. S. and | |
| Silva, Nadia F. F. and | |
| Siqueira, Felipe and | |
| Albuquerque, Hidelberg O. and | |
| Gomes, Juliana R. S. and | |
| Souza, Ellen and | |
| Lima, Eliomar A.", | |
| editor = "Gamallo, Pablo and | |
| Claro, Daniela and | |
| Teixeira, Ant{\'o}nio and | |
| Real, Livy and | |
| Garcia, Marcos and | |
| Oliveira, Hugo Gon\({\c{c}}\)alo and | |
| Amaro, Raquel", | |
| booktitle = "Proceedings of the 16th International Conference on Computational Processing of Portuguese", | |
| month = mar, | |
| year = "2024", | |
| address = "Santiago de Compostela, Galicia/Spain", | |
| publisher = "Association for Computational Lingustics", | |
| url = "https://aclanthology.org/2024.propor-1.38", | |
| pages = "374--383", | |
| } | |
| ``` | |